Method for validating specified prices on real property

ABSTRACT

A computer-implemented method for validating specified prices on real property. A set of real estate properties comparable to the subject property are retrieved. A measurement of similarity between each comparable property and the subject property is then determined. A plurality of adjustment rules are then applied to adjust the price of the comparable properties. The adjusted comparable properties are then extracted, sorted, and ranked, according to the specified sale price. The extracted comparable properties are then aggregated into an estimate price of the subject property. After aggregation, the estimate price of the subject property is compared to the specified price and a measurement of confidence validating the reliability of the specified price is then generated.

CROSS-REFERENCES TO RELATED APPLICATIONS

This is a continuation-in-part of application Ser. No. 08/519,380 filedAug. 25, 1995, now abandoned.

This application is related in subject matter to application Ser. No.09/118,112 filed July 17, 1998 now pending, and application Ser. No.09/118,188 filed Jul. 17, 1998 now pending.

FIELD OF THE INVENTION

This invention relates generally to real estate appraisals and moreparticularly to a method for validating specified prices on realproperty.

Real estate appraisals are used to estimate the defined value of a realproperty interest in real estate. The appraisals have use in many typesof real estate transactions. For example, a buyer may use an appraisalto find out a property's market value before accepting a selling price,a seller may use an appraisal to determine a selling price, an insurermay use an appraisal before underwriting a mortgage loan, or a lendermay use an appraisal to acquire certain information about a propertybefore issuing a loan for that property. A problem with appraisals isthat they can take a lot of time (i.e. about four days) to complete,which may be too long in many real estate transactions. For example, inthe scenario of a lender determining whether to issue a loan to a buyerwho has agreed to a specified price with a seller, the lender willprovide the appraiser with the location of the subject property (i.e.,the real property to be appraised) and the specified price and requestthat an appraisal report be prepared as soon as possible. The appraisaltakes about four days because the appraiser needs to inspect the subjectproperty, find recent sales that are comparable to the subject property,determine the comparables which are the most relevant to the subjectproperty, adjust the sales prices of the most relevant comparables toreflect their differences from the subject property, reconcile theadjusted sales prices to derive a single value estimate of the subjectproperty, and then decide whether the specified price is a valid price.In many cases a full appraisal is not needed. In these cases, all thatis required is a determination of whether the specified price is areasonable value for the subject property. Presently, there are noapproaches that determine if the specified price is reasonable.Therefore, there is a need for a method that determines whetherspecified prices on real property interests are reasonable.

SUMMARY OF THE INVENTION

Thus, in accordance with the present invention, there is provided acomputer-implemented method for validating a specified price on asubject property. The computer-implemented method comprises retrieving aset of real estate properties comparable to the subject property from acase base. The comparable real estate properties and the subjectproperty are characterized by a plurality of common attributes eachhaving a respective value. Each attribute value from the set ofcomparable properties is evaluated to the same attribute value of thesubject property on a fuzzy preference scale indicating desirable andtolerable deviations from an ideal match with the subject property. Eachevaluation generates a preference vector having a value between 0 and 1.A measurement of similarity between each comparable property and thesubject property is then determined. Additional attributescharacterizing the comparable properties are then examined with thesubject property. Next, the present invention determines the differencesbetween the additional attributes characterizing each of the comparableproperties and the subject property. A plurality of adjustment rulesfrom an adjustment rule database are then applied to the differencesbetween each of the comparable properties and the subject property. Theplurality of adjustment rules adjust the price of the comparableproperties by either decreasing the price of each comparable property ifthe comparable property has differences in the additionalcharacteristics that are superior in value to the subject property orincreasing the price of each comparable property if the comparableproperty has differences in additional characteristics that are inferiorin value to the subject property. The adjusted comparable properties arethen extracted according to a predetermined threshold. The adjustedcomparable properties are then sorted and ranked according to similaritywith the specified price. The sorted and ranked comparable propertiesare then extracted. The extracted comparable properties are thenaggregated into an estimate price of the subject property. Afteraggregation, the estimate price of the subject property is compared tothe specified price and a measurement of confidence validating thereliability of the specified price is then generated.

While the present invention will hereinafter be described in connectionwith an illustrative embodiment and method of use, it will be understoodthat it is not intended to limit the invention to this embodiment.Instead, it is intended to cover all alternatives, modifications andequivalents as may be included within the spirit and scope of thepresent invention as defined by the appended claims.

DESCRIPTION OF THE DRAWINGS

FIG. 1 is a flow chart describing the steps of validating specifiedprices on real property according to this invention;

FIG. 2 is a system for validating specified prices on property accordingto this invention;

FIG. 3 is a flow diagram illustrating the operations performed in thesystem shown in FIG. 2;

FIG. 4 is a graphical display illustrating the preference criteria usedin this invention; and

FIG. 5 is an example of a similarity distribution for a set ofcomparable properties.

DETAILED DESCRIPTION OF THE INVENTION

This invention validates the specified price of a subject property byusing case-based reasoning principles. In particular, case-basedreasoning is used to automate the steps of finding recent salescomparable to the subject property, determining the most relevant unitsof comparison, comparing the subject property with the comparables,adjusting the sales price of the comparables to reflect the differencesfrom the subject, and reconciling the adjusted sales prices of thecomparables to derive an estimate of the subject. FIG. 1 is a flow chartdescribing the steps of validating specified prices on real propertyaccording to this invention. In FIG. 1, an initial set of real estateproperties that are comparable to the subject property are retrieved at10. The initial set of comparable properties and the subject propertyare both characterized by a plurality of common attributes each having arespective value. The attributes include transaction characteristicssuch as location of the property, date of sale of the property, saleprice of the property, the living area, the lot size, the number ofbedrooms, and the number of bathrooms. Although the illustrativeembodiment is described with reference to these attributes, it is withinthe scope of this invention to use other attributes such as type ofconstruction of the property, parking spaces, location influence of theproperty, type of construction of the property, foundation of theproperty, the roof type and roof cover of the property, garage orcarport, style of the property, etc. The number of comparable propertiesare filtered at 12 to reduce the number of potential comparables. Eachattribute value from the filtered comparable properties is thenevaluated to the same attribute value of the subject property and ameasure of similarity is then generated at 14. The price of each of thecomparable properties is then adjusted at 16 to the value of the subjectproperty by applying a set of modification rules. The modification rulesevaluate additional characteristics between the comparable propertiesand the subject property and adjust the price of the propertyaccordingly. In the illustrative embodiment, the additionalcharacteristics are the number of fireplaces, pools, the effective ageof the properties, the quality of the properties, and the condition ofthe properties. After price adjustment, a smaller set of more closelyrelated comparable real estate properties is then extracted at 18. Theextracted comparable properties are then aggregated at 20 into anestimate price of the subject property. After the estimate price hasbeen generated, the price is compared to the specified price todetermine if it is a valid price. A measurement of confidence indicatingthe reliability of the validation is then generated at 24.

FIG. 2 shows a system 26 for validating specified prices on propertyaccording to this invention. The system 26 includes a comparableproperty database 28, which is preferably a case base having a pluralityof properties. The system 26 also includes an adjustment rules database30 containing rules for adjusting the prices of the comparableproperties in the comparable property case base 28. A personal computeror work station 32 having a hard drive 34, an input device such as akeyboard 36 and a mouse 38, and an output device such as a display 40and a printer 42, is connected to the case base 28 and the database 30.The computer 32 uses SQL queries to retrieve the comparable propertiesfrom the case base 28 and performs a series of case adaptationoperations to the properties according to the adjustment rules.

The case retrieval and case adaptation operations are shown in furtherdetail in the flow diagram of FIG. 3. After information about thesubject property has been acquired, similar comparable real estateproperties are selected at 44 from the case base 28. In the illustrativeembodiment, the case base 28 contains about 600,000 real estateproperties, with each property being characterized by about 166attributes. Typically, the selection at 44 returns anywhere from four toone hundred comparable properties. The selection is performed bycomparing specific attributes (i.e., location, date of sale, sale price,living area, lot size, number of bedrooms, and number of bathrooms) ofthe subject property with the same attributes of each comparableproperties. All of the retrieved potential comparable properties havevalues that are within allowable deviations for the subject property. Ifthe size of the comparable set of properties is too small (e.g., lessthan 10), then the allowable deviations can be adjusted so that morecomparables of lesser quality can be obtained.

After the initial set of comparable properties has been retrieved, eachof the values for the attributes (i.e., location, date of sale, saleprice, living area, lot size, number of bedrooms, and number ofbathrooms) are evaluated against the same attributes of the subjectproperty on a fuzzy preference scale that indicates desirable andtolerable deviations from an ideal match. For example, in theillustrative embodiment, the maximum allowable deviations for theattributes are within one mile for the location attribute, 12 months forthe date of sale attribute, plus or minus 25% for the sale priceattribute, plus or minus 25% for the living area attribute, plus 100% orminus 50% for the lot size attribute, plus or minus two percent for thenumber of bedrooms attribute, and plus or minus two percent for thenumber of bathrooms attribute. After each attribute is evaluated, apreference vector having a value between 0 and 1 inclusive, isgenerated, with 1 being the best value. These values represent thepartial degree of membership of each attribute value in the fuzzy setsand fuzzy relations representing the preference criteria provided in thefuzzy preference scales.

An understanding of the above preference criteria for the first fiveattributes (i.e., the date of sale, the distance from subject property,the sale price, the living area, and the lot size) is graphicallydescribed in FIG. 4. Each of the attributes in FIG. 4 have a trapezoidalshape representing its criteria evaluation functions. For eachattribute, the broader base of the trapezoidal shape represents therange of tolerable values and corresponds to the interval-value used inthe preliminary retrieval query. The smaller top or core of thetrapezoidal shape represents the most desirable range of values andestablishes the top preference for the attribute. An attribute valuefalling inside the most desirable region will receive a preference valueof 1. As the feature value moves away from the most desirable range, itsassociated preference value will decrease from 1 to 0. At the end ofthis evaluation, each comparable will have a preference vector, witheach element taking values in the [0,1] interval. These values representthe partial degree of membership of each attribute value in the fuzzysets and fuzzy relations representing the preference criteria providedin the fuzzy preference scales. Typically, comparable propertiesselected in the preliminary retrieval that have attribute values fallingoutside the tolerable value range will not be evaluated.

In the illustrative embodiment, the preference distribution for thedate-of-sale attribute for a comparable property that was sold withinthree months of the present date is 1. If the date of sale of thecomparable property was 6 months ago, its preference value will be 0.67.If the date of sale of the comparable property was 9 months ago, itspreference value will be 0.33. Any comparable property with a date ofsale of more than 12 months is given a preference value of zero. For thedistance from the subject property attribute, comparable propertieslocated within 0.25 miles from the subject property have a preferencevalue of 1. If the comparable property is located a half of a mile fromthe subject property, then its preference value will be 0.67. If thecomparable property is located three quarters of a mile from the subjectproperty, then its preference value will be 0.33. Any comparableproperty located more than one mile from the subject property is given apreference value of zero. For the sale price attribute, a comparableproperty having a sale price that is within 87.5% to 112.5% of thespecified price of the subject property or a price provided by anotherestimator has a preference value of 1. If the comparable property has asale price that is within 87.5% to 75% or within 112.5% to 125% of thespecified price of the subject property or the sale price provided byanother estimator, then the comparable property is given a preferencevalue between zero and 1. If the comparable property has a sale pricethat is less than 75% or greater than 125% of the specified price of thesubject property or the price provided by another estimator, then thecomparable property is given a preference value of zero. For the livingarea attribute, a comparable property having a living area that iswithin 94% to 106% of the living area of the subject property will havea preference value of 1. If the comparable property has a living areathat is within 75% to 94% or within 106% to 125% of the living area ofthe subject property, then the comparable property is given a preferencevalue between zero and 1. If the comparable property has a living areathat is less than 75% or greater than 125% of the living area of thesubject property, then the comparable property is given a preferencevalue of zero. For the lot size attribute, a comparable property havinga lot size that is within 87.5% to 112.5% of the lot size of the subjectproperty will have a preference value of 1. If the comparable propertyhas a lot size that is within 50% to 87.5% or within 112.5% to 150% ofthe lot size of the subject property, then the comparable property isgiven a preference value between zero and 1. If the comparable propertyhas a lot size that is less than 50% or greater than 150% of the lotsize of the subject property, then the comparable property is given apreference value of zero. The tolerable and desirable ranges of valuesfor the five attributes are illustrative of possible values for use withthis invention and are not intended to be limiting.

The remaining two attributes not shown in FIG. 4, the number of bedroomsand the number of bathrooms, have preference functions which areillustrated in Tables 1 and 2, respectively. For example, if the subjectproperty has five bedrooms, then Table 1 will provide a preference valueof 1 for comparable properties having five bedrooms. However, if thecomparable property has six or more bedrooms, then the comparable willbe given a preference value of 0.80. Also, Table 1 indicates that acomparable property having four bedrooms will have a preference value of0.60, three bedrooms will have a preference value of 0.50, and two orless bedrooms will receive a preference value of zero.

                  TABLE 1                                                         ______________________________________                                        Preference Functino for Number of Bedrooms                                              Comparable's # Bedrooms                                                           1      2      3    4      5    6+                               ______________________________________                                        Subject's                                                                             1     1.00   0.50   0.05 0.00   0.00 0.00                               # Bedrooms 2 0.20 1.00 0.50 0.05 0.00 0.00                                     3 0.05 0.30 1.00 0.60 0.05 0.00                                               4 0.00 0.05 0.50 1.00 0.60 0.20                                               5 0.00 0.00 0.05 0.60 1.00 0.80                                               6+ 0.00 0.00 0.00 0.20 0.80 1.00                                           ______________________________________                                    

Table 2 can be used in a similar manner to generate preference functionsfor the number of bathrooms attribute. For example, if the subjectproperty has 2 bathrooms, then Table 2 will provide a preference valueof 1 for comparable properties having two bathrooms. However, if thecomparable property has two and a half bathrooms, then the comparablewill be given a preference value of 0.70. Also, Table 2 indicates that acomparable property having three bathrooms will have a preference valueof 0.25, three and half bathrooms will have a preference value of 0.05,four or more bathrooms will have a preference value of zero. Inaddition, Table 2 indicates that a comparable property having one and ahalf bathrooms will have a preference value of 0.70 and one bathroomwill have a preference value of 0.1.

                  TABLE 2                                                         ______________________________________                                        Preference Function for Number of Bathrooms                                         Comparable                                                              Subject                                                                             1      1.5    2    2.5  3    3.5  4    4.5  5+                          ______________________________________                                        1     1.00   0.75   0.20 0.05 0.01 0.00 0.00 0.00 0.00                          1.5 0.60 1.00 0.60 0.25 0.10 0.05 0.00 0.00 0.00                              2 0.10 0.70 1.00 0.70 0.25 0.05 0.00 0.00 0.00                                2.5 0.05 0.20 0.75 1.00 0.75 0.20 0.05 0.00 0.00                              3 0.01 0.10 0.40 0.80 1.00 0.80 0.40 0.10 0.05                                3.5 0.00 0.05 0.15 0.45 0.85 1.00 0.85 0.45 0.30                              4 0.00 0.00 0.05 0.20 0.50 0.90 1.00 0.90 0.70                                4.5 0.00 0.00 0.00 0.10 0.30 0.70 0.95 1.00 0.95                              5+  0.00 0.00 0.00 0.05 0.15 0.35 0.75 0.95 1.00                            ______________________________________                                    

After each attribute of the comparable real estate properties has beenevaluated against the subject property and a preference vector has beengenerated, the measurement of similarity between each comparable and thesubject property is determined. The measurement of similarity is afunction of the preference vector computed above and of the prioritiesof the attributes, which are reflected by a set of predeterminedweights. The predetermined weights for the illustrative embodiment areshown in Table 3 under the weight column. In the illustrativeembodiment, the living area attribute has a weight of 0.3, the date ofsale and distance attributes both have a weight of 0.2, the price andlot size attributes have a weight of 0.1, while the number of bedroomsand bathrooms attributes have a weight of 0.05.

The measurement of similarity for a comparable property is determined bymultiplying the predetermined weight by the preference vector generatedfor each attribute. This product results in a weighted preference value.After all of the weighted preference values have been determined, theweighted preferences are summed together to generate the measurement ofsimilarity. An example of a measurement of similarity computationbetween a comparable property and a subject property is provided inTable 3. In the example provided in Table 3, the subject property has aprice of $200,000, a living area of 2000 square feet, a lot size of20,000 square feet, three bedrooms, and two and a half bathrooms. Thecomparable property was sold six months ago, is located 0.2 miles fromthe subject property, sold for $175,000, has a living area of 1800square feet, a lot size of 35,000 square feet, three bedrooms and twobathrooms. A comparison between the subject property and the comparableproperty is provided in the fourth column for each attribute. In Table3, the price comparison is 87.50%, the living area comparison is 90%,the lot size comparison is 175%, and the number of bedroom comparison is0%. As described above, each comparison results in a preference which ismultiplied by the predetermined weight. The weighted preferences foreach attribute for the comparable property are listed in the weightedpreference column and the measurement of similarity is the sum of theweighted preferences. In Table 3, the measurement of similarity for thisparticular comparable property is 0.7915.

                                      TABLE 3                                     __________________________________________________________________________    Similarity Measurement Computation                                                                           Weighted                                         Attribute Subject Comparable Comparison Preference Weight Preference        __________________________________________________________________________    Date of Sale                                                                        x   6 months                                                                            6 months                                                                            0.67 0.2 0.134                                            Distance x 0.2 miles.sup.   0.2 miles.sup.  1 0.2 0.2                         Living Area 2000 1800 90% 0.79 0.3 0.237                                      Lot Size 20000 35000 175% 0.33 0.1 0.033                                      Sale Price 200000 175000 88% 1 0.1 0.1                                        # Bedrooms 3 3 3->3  1 0.05 0.05                                              # Bathrooms 2.5 2 2.5->2  0.75 0.05 0.0375                                    Similarity      0.7915                                                      __________________________________________________________________________

After the measurement of similarities have been computed for all of thecomparable properties, the comparables are then sorted in decreasingorder of similarity. After sorting, the comparables are arranged in apreference distribution as shown in FIG. 5, with the comparable propertyhaving the highest measurement of similarity placed at one end of thedistribution and the comparable property having the lowest measurementof similarity placed at the opposite end of the distribution. Thecomparable properties are then compared against a predeterminedthreshold that reflects desirable and tolerable deviations of an idealmatch with the subject property. More specifically, the comparableproperties that have a measurement of similarity above the predeterminedthreshold will be extracted for further review, while the comparableproperties below the threshold are removed from further consideration.FIG. 5 shows two possible similarity distributions for two differentretrievals. In these distributions, a value of 0.5 is used as thepredetermined threshold. Therefore, comparable properties having ameasurement of similarity above 0.5 are extracted for further review,while the comparables with measurements of similarities less than 0.5are removed and no longer considered. In FIG. 5, retrieval number onehas 11 comparable properties having a measurement of similarity above0.5, while retrieval number two has five comparable properties with ameasurement of similarity above 0.5.

Instead of using a predetermined threshold to determine which retrievalprovides the best results, an alternative approach is to take theaverage of the similarity values of the retrieved comparables. Thiscorresponds to the area under the curve of the distributions and isdetermined by taking the average measurement of similarity. For example,the average similarity measure for retrievals one and two in FIG. 5would be determined as follows:

Average Similarity Measure Subject 1 (from best 8 comps):

(1+1+0.85+0.8+0.7+0.7+0.7+0.5)/8=0.78125

Average Similarity Measure Subject 2 (from best 8 comps):

(1+0.9+0.8+0.7+0.7+0.4+.035+0.25)/8=0.6375

Referring again to FIG. 3, the comparable properties that have beenselected for further review at 44 are then adjusted to reflect the valueof the subject property at 46. In particular, any difference between thesubject property and the comparable properties that would cause thecomparables to be more or less valuable than the subject property willrequire an adjustment. Thus, if a comparable property is superior to thesubject property, then an adjustment is needed to decrease the price ofthe comparable. However, if the comparable property is inferior to thesubject property, then an adjustment is needed to increase the price ofthe comparable.

The adjustments to the price of the comparable properties are performedby using a plurality of adjustment rules stored in the adjustment ruledatabase 30. The adjustment rules are generated from the plurality ofattributes stored in the case base 28 for all of the comparableproperties. As mentioned earlier, there are approximately 166 attributesavailable for the subject property and the comparable properties in theillustrative embodiment. A illustrative listing of the attributes arepresented below. The attributes described with a # are numeric and theremaining attributes are textual. The numeric attributes are describedwith a number and the textual attributes are described with text. Forexample, the attribute total room is described with a number such asthree, four, or the like, and the pool attribute is described with atext format such as indoor, spa, etc.

    ______________________________________                                        Recording Date                                                                           YYMMDD                                                               SalePrice # in hundreds                                                       SaleCode (Verified, Full, Unconfirmed, Approximate,                            Partial, Confirmed, Non-valid)                                               SFRTotalRooms #                                                               SFRFullBaths #                                                                SFRHalfBaths # (number of half baths)                                         SearchableBaths # Full + Half Baths (1 full + 1 half = 2 baths)                         SFRFireplaces #                                                     SFRStyle (coloniAl, Bungalow, Cape, D--contemporary,                           E--ranch, F--tudor, G--mediterranian,                                         H--georgian, I--high ranch, J--victorian,                                     K--conventional, L--a frame)                                                 SFRBedrooms #                                                                 Pool (C--pool/spa, E--enclosed, Z--solar, H--heated,                           I--indoor, P--pool, S--spa, V--vinal)                                        LotArea # (sq ft)                                                             BuildingArea #                                                                NumberOfUnits #                                                               NumberOfStories #/10 (0.15 = 1.5 stories)                                     ParkingSpaces #                                                               LocationInfluence (A--positive view, B--ocean, C--bay front,                   D--canal, E--river, F--lake/pond, G--wooded,                                  H--golf, I--corner lot/sound, J--corner,                                      K--cul-de-sac, L--greenbelt, N--negative)                                    TypeOfConstruction (A--frame, B--concrete, C--masonry, D--brick,                         E--stone, F--concrete block, G--manufact,                           H--metal, I--others, J--adobe, K--dome, L--log,                               M--special, N--heavy, O--light, S--steel)                                    Foundation (C--concrete, S--slab, L--mud sill, M--masonry,                     P--piers, R--crawl/raised)                                                   YearBuilt # 19XX                                                              EffectiveYearBuilt # 19XX                                                     Quality (Average, Excellent, Fair, Good, Poor, Luxury)                        Condition (Average, Excellent, Fair, Good, Poor, None)                        AirCondition (Central, Evaporative, Heat pump, WaLl, None,                     Office only, Partial, Window, Yes, Z-chill water)                            Heating (A--gravity, B--forced air, C--floor furnace,                          D--wall furnace, E--hot water, F--ele bboard,                                 G--heat pump, H--steam, I--radiant, J--space                                  heater, K--solar, L--none, P--partial, Y--yes,                                Z--Central)                                                                  ParkingType (A--Attached, B--built in, C--carport,                             D--detached, E--basement, F--off-site, G--open,                               H--none, J--finished, K--covered, P--paved,                                   Q--adequate, R--roof, S--subterranean,                                        U--unimproved, Y--yes, Z--garage)                                            BasementArea #                                                                RoofType (A--arched, F--flat, G--gable, H--hip,                                M--mansard, T--truss-jois)                                                   RoofCover (A--mood shingles, B--mood shake, C--composite                       shingle, D--asbestos, E--built up, F--tar+gravel,                             G--slate, H--rock+gravel, I--tile, J--other,                                  R--roll, S--steel, Y--concrete)                                              Frame (C--concrete, S--steel, M--masonry, W--wood)                            GarageCarportSqFt #                                                           latitude #                                                                    longitude #                                                                 ______________________________________                                    

Based on these attributes, the following adjustment rules are generatedin the case base 28 and stored in the adjustment rule database 30.

RecordingDate none

SalePrice

SaleCode ?

SFRTotalRooms none

SFRTotalBaths see Table 4

                                      TABLE 4                                     __________________________________________________________________________    Adjustment Function for Number of Bathrooms                                       Comp                                                                      Subject                                                                           1   1.5                                                                              2  2.5 3   3.5 4   4   5+                                          __________________________________________________________________________    1   0.00                                                                              -1.50                                                                            -3.00                                                                            -5.00                                                                             -8.00                                                                             N/A N/A N/A N/A                                           1.5 1.00 0.00 -1.00 -3.50 -6.00 -9.00 N/A N/A N/A                             2 4.00 1.50 0.00 -2.25 -4.00 -6.50 N/A N/A N/A                                2.5 7.00 4.50 2.00 0.00 -2.00 -4.50 -7.00 N/A N/A                             3 9.00 6.50 3.00 2.00 0.00 -2.50 -5.00 -7.50 '@*-5                            3.5 N/A 8.50 6.50 4.50 2.50 0.00 -3.00 -5.50 '@*-5                            4 N/A N/A 8.50 7.00 5.50 3.00 0.00 -3.00 '@*-5                                4.5 N/A N/A N/A 10.00 8.00 6.00 3.00  0.00 '@*-5                              5+ N/A N/A N/A '@*-5 '@*-5 '@*-5 '@*-5 '@*-5 0.00                           __________________________________________________________________________

In order to accommodate for even more or less bathrooms, Table 4 takesthe difference between the subject property and the comparable property(i.e., @) and multiplies the difference by five. For example, if thesubject property has seven bathrooms and the comparable has three, thenthe adjustment would be 20 ([7-3]*5). If the subject property has threebathrooms and the comparable has seven, then the adjustment would be -20([7-3]*-5).

SFRFireplaces (subject-comp)*2000

SFRStyle ?

SFRBedrooms see Table

                  TABLE 5                                                         ______________________________________                                        Adjustment Function for Number of Bedrooms                                      Sub-   Comp                                                                           ject 1     2    3    4       5       6+                             ______________________________________                                        1    0.00    0.00   -3.50                                                                              N/A     N/A     N/A                                    2 0.00 0.00 0.00 -2.50  N/A N/A                                               3 4.00 0.00 0.00 0.00 -4.00  N/A                                              4 N/A 4.00 0.00 0.00 0.00 '(@-1)*3.5                                          5 N/A N/A 4.00 0.00 0.00 '(@-1)*3.5                                           6+ N/A N/A N/A '(@-1)*3.5 '(@-1)*3.5 0.00                                   ______________________________________                                    

In order to accommodate for even more or less bedrooms, Table 5 takesthe difference between the subject property and the comparable property(i.e., @) and subtracts the difference by one and multiplies thedifference by 3.5. For example, if the subject property has six bedroomsand the comparable has four, then the adjustment would be3.5[[(6-4)-1]*3.5]. If the subject property has four bedrooms and thecomparable has six, then the adjustment would be -3.5[[(6-4)-1]*-3.5].

    ______________________________________                                        Pool       $10000 for a pool                                                    LotArea (subject - comp)                                                      BuildingArea (subject - comp) * (22 +                                          (sales.sub.-- price.sub.-- closing.sub.-- of.sub.-- comp * .00003))                    NumberOfUnits ?                                                     NumberOfStories ?                                                             ParkingSpaces ?                                                               LocationInfluence no adjustment between comps in same level                    (B--ocean, F--lake/pond, A--positive view,                                    C--bay front = +10%, D--canal, E--river,                                      G--wooded, H--golf, L--greenbelt = +5%                                        K--cul-de-sac, J--corner = no adjust                                          I--corner lot/sound, N--negative = -5%)                                      TypeOfConstruction ?                                                          Foundation ?                                                                  YearBuilt use only if no effective year built w *                              (Age.sub.-- comp-Age.sub.-- subject) * (SalePrice.sub.-- comp/                          1000)                                                               if (Age.sub.-- subject + Age.sub.-- comp)/2 < 5 then w = 3.2                  else if (Age.sub.-- subject + Age.sub.-- comp)/2 < 9 then w =                 2.4 else if (Age.sub.-- subject + Age.sub.-- comp)/2 < 12                     then w = 1.6 else if (Age.sub.-- subject + Age.sub.-- comp)/                  2 < 20 then w = .8 else w = .4                                                max of 10% of salePrice                                                      EffectiveYearBuilt w * (Age.sub.-- comp-Age.sub.-- subject) *                  (SalePrice.sub.-- comp/1000)                                                  if (Age.sub.-- subject + Age.sub.-- comp)/2 < 4 then w = 4                    else if (Age.sub.-- subject + Age.sub.-- comp)/2 < 6 then w =                 3 else if (Age.sub.-- subject + Age.sub.-- comp)/2 < 8 then                   w = 2 else if (Age.sub.-- subject + Age.sub.-- comp)/2 < 15                   then w = 1 else w = .5 max of 10% of salePrice                                Quality(.02 * sale price) for each level of difference                        (Luxury > Excellent > Good > Average > Fair >                                 Poor) Condition (.02 * sale price) for each level of                          difference (Excellent > Good > Average > Fair >                               Poor)                                                                        AirCondition (.01 * sale price) for each level of difference                   (Central > Evaporative, Heat pump, waLl, Yes, Z--                             chill water > None, Office only, Partial, Window,)                           Heating (.01 * sale price) for each level of difference                        (Z--Central, B--forced air > A--gravity, C--                                  floor furnace, D--wall furnace, E--hot water,                                 F--ele bboard, G--heat pump, H--steam,                                        I--radiant, J--space heater, K--solar, Y--yes >                               L--none, P--partial)                                                         ParkingType ?                                                                 BasementArea if not finished 1/4 to 1/2 value of living area                   if finished 1/2 to 1 value of living area                                    RoofType ?                                                                    RoofCover ?                                                                   Frame ?                                                                       GargageCarportSqFt ?                                                          latitude none                                                                 longitude none                                                              ______________________________________                                    

These adjustment rules are then applied to the comparable propertiesselected at 40 in order to adjust for the value of the subject property.Instead of applying all of the above adjustment rules, time can be savedby only applying several of the adjustment rules deemed to be moreimportant than the others, such as the adjustment rules for theattributes of fireplaces, a pool, the effective age of the property,quality of the property, and condition of the property.

An example of an adjustment for a comparable property is provided inTable 6. In the example provided in Table 6, the comparable property hasa sale price of $175,000 dollars. However, the comparable property has abuilding area of 1800 square feet, while the subject property has abuilding area of 2000. Using the adjustment rules for the attributebuilding area, the price of the comparable is adjusted by $5450 (i.e.,22+(175000 * 0.00003)=$27.25 per square foot which is (200*$27.25=$5450)). Also, the price of the comparable is adjusted for thelot area since the comparable has a larger lot size. In Table 6, the lotarea attribute is adjusted by $1/sq ft for a total of -$5000. Since thecomparable has two bathrooms and the subject property has two and a halfbathrooms, the price needs to be adjusted by using the rules provided inTable 4, which turns out to be $2000. There are no adjustments necessaryfor the bedroom attribute because both the subject property and thecomparable property have the same number of bedrooms. Since thecomparable does not have a fireplace and the subject property has one,the price needs to be adjusted accordingly. Using the adjustment rulefor fireplaces, the price is adjusted $2000. If the adjustment rules areused for the effective year, quality, condition, and pool attributes forthe subject and comparable property, the rules will generate anadjustment of $2800, $3500, $0, and $10,000, respectively. All of theadjustments are then summed with the sale price of the comparableproperty to arrive at the adjusted price. In Table 6, the adjusted priceof the comparable property is $195,750.

                  TABLE 6                                                         ______________________________________                                        Example of an Adjustment                                                          Attribute  Subject    Comparable                                                                            Adjustment                                  ______________________________________                                        SalePrice  ?          175000    175000                                          BuildingArea 2000 1800 5450                                                   LotArea 20000 25000 -5000                                                     SFRTotalBaths 2.5 2 2000                                                      SFRBedrooms 3 3                                                               SFRFireplaces 1 0 2000                                                        EffYearBuilt 93 89 2800                                                       Quality Good Average 3500                                                     Condition Average Average                                                     Pool Yes No 10000                                                                195750                                                                   ______________________________________                                    

Referring again to FIG. 3, after all of the adjustments are applied tothe sales price of the comparable properties, another set of comparableproperties that more closely match the subject property are extracted at48. In the illustrative embodiment, 4-8 comparables are selected at 48.If less than four comparables are selected, then the comparables may notcorrectly reflect the market and if more than eight comparables areused, then some of the comparables may not be similar enough to thesubject property.

The best (i.e., four to eight) of the remaining adjusted comparableproperties are selected by sorting the comparables according to theiradjusted prices in the manner as shown in Table 7. The comparables withthe highest adjusted price are placed at the top and ranked indescending order. The third column in table 7 represents the differencebetween the adjusted price of the comparable and the specified price ofthe subject. The four to eight properties with the smallest differenceare selected as the final set of comparables.

                  TABLE 7                                                         ______________________________________                                        Selection of the best Comparables                                               Property        Adjusted Price                                                                           Difference                                       ______________________________________                                        342-837       214400     14400                                                  113-012 204500 4500                                                           306-018 201400 1400                                                           093-018 200600 600                                                            305-006 200400 400                                                            685-046 200200 200                                                            847-984 199750 250                                                            873-005 199600 400                                                            431-023 199000 1000                                                           331-018 197000 3000                                                         ______________________________________                                    

Referring again to FIG. 3, after the best of the adjusted comparableshave been selected, the adjusted prices of the selected comparables areaggregated into an estimate price of the subject property at 50. Theaggregated estimated price is determined by multiplying the adjustedprice of the comparable properties to their respective measurement ofsimilarity and summed together to generate a total weighted price. Next,the total weighted price is divided by the total of the similaritymeasurements for the comparable properties. The result is an estimateprice of the subject property. An example of the aggregation forcomparables is provided in Table 8. In this example, the total weightedprice is $757,640 and the total similarity score is 3.83. Thus, dividing$757,640 by 3.83 results in an estimate price of 199,900 for the subjectproperty.

                  TABLE 8                                                         ______________________________________                                        Comparable Aggregation                                                            Comparable                                                                              Adjusted Price                                                                              Score                                                                              Weighted Price                               ______________________________________                                        113-012   197000        0.95   187150                                           306-008 202000 0.88 177760                                                    093-011 196500 0.78 153270                                                    685-046 192000 0.64 122880                                                    847-984 201000 0.58 116580                                                    total  3.83 757640                                                          final estimate = 757640/3.83 =                                                                       199900                                                 ______________________________________                                    

After producing the final estimate of the value of the subject property,the estimate is compared against the specified price for validation at52. A measurement of confidence indicating the reliability of thevalidation is then generated at 54. In particular, the confidencemeasurement in the estimate can be obtained by averaging the similarityscores of the comparables in the final selection, or by averaging thenumber of comparables over a threshold in the primary retrieval. Theestimate is justified by displaying the comparables in enough detail sothat they can be shown to be similar to the specified price of thesubject.

It is therefore apparent that there has been provided in accordance withthis invention, a method for validating the price of a real estatesubject property based on a specified price that fully satisfy the aimsand advantages and objectives hereinbefore set forth. The invention hasbeen described with reference to several embodiments, however, it willbe appreciated that variations and modifications can be effected by aperson of ordinary skill in the art without departing from the scope ofthe invention. For example, the present invention can be used tovalidate the estimated price generated by a conventional estimator.

What is claimed is:
 1. A computer-implemented method for validating aspecified price of a subject property, comprising:retrieving a set ofreal estate properties comparable to the subject property from a casebase, the comparable properties and the subject property characterizedby a plurality of common attributes each having a respective value;evaluating each attribute value from the set of comparable properties tothe same attribute value of the subject property on a fuzzy preferencescale indicating desirable and tolerable deviations from an ideal matchwith the subject property, each evaluation generating a preferencevector having a value between 0 and 1; determining a measurement ofsimilarity between each comparable property and the subject property;examining additional attributes characterizing the comparable propertieswith the subject property; determining differences between theadditional attributes characterizing each of the comparable propertiesand the subject property; applying a plurality of adjustment rules froman adjustment rule database to the differences between each of thecomparable properties and the subject property, the plurality ofadjustment rules adjusting the price of the comparable properties byeither decreasing the price of each comparable property if thecomparable property has differences in the additional characteristicsthat are superior in value to the subject property or increasing theprice of each comparable property if the comparable property hasdifferences in additional characteristics that are inferior in value tothe subject property; extracting the adjusted comparable propertiesaccording to a predetermined threshold; sorting and ranking the adjustedcomparable properties according to similarity with the specified price;extracting the sorted and ranked comparable properties; aggregating theextracted comparable properties into an estimate price of the subjectproperty; and comparing the estimate price of the subject property tothe specified price and generating a measurement of confidencevalidating the reliability of the specified sale price.
 2. Thecomputer-implemented method according to claim 1, further comprisingfiltering the set of comparable properties to obtain a smaller set ofcomparable properties.
 3. The computer-implemented method according toclaim 1, wherein the plurality of common attributes comprise date ofsale, distance to each other, sale price, living area, lot size, numberof bedrooms, and number of bathrooms.
 4. The computer-implemented methodaccording to claim 1, determining a measurement of similarity comprisesproviding a predetermined weight to each attribute, multiplying thepredetermined weight by the preference vector for each attribute togenerate a weighted preference value, and summing each of the weightedpreference values to provide a measurement of similarity.
 5. Thecomputer-implemented method according to claim 1, wherein the additionalcharacteristics comprise fireplaces, a pool, effective age of theproperty, quality of the property, and condition of the property.
 6. Thecomputer-implemented method according to claim 1 wherein the aggregatingcomprises multiplying the adjusted price of the comparable properties totheir respective measurement of similarity to generate a weighted price,summing the weighted prices for all of the comparable properties togenerate a total weighted price, summing the measurements ofsimilarities from the comparable properties to generate a totalmeasurement of similarity, dividing the total weighted price by thetotal measurement of similarity to generate the estimate price value ofthe subject property.